Background

Notes and format last updated May 7, 2020

Starting on the May 7th update, the NY Times began including probable covid cases/deaths along with confirmed. This mostly affects death counts – for certain geographies that include probable COVID deaths in addition to confirmed, these are now added to the totals. For the time being, they were all added to the May 6th totals, causing a big spike at the U.S. level. Over time, NY Times will revise their historical counts and distribute these added deaths when they actually occurred, so the spike should fade.

Growth rates

Heat maps

  • The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
  • The first plot compares growth rate for total cases; the second, growth rate for total deaths.
  • The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
  • The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
    • You can use the plots to track each geography over time and to compare the geographies to one another.
    • You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.

Case growth rates

  • This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of cases, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new cases) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new case reporting at the state level.
    • For total cases, the trendlines are a rolling 3-day average of daily growth rates in total cases. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total cases have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total case line get as close to zero as possible.
    • For new cases, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new cases. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total cases, we want to watch for the lines for new cases to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis.

U.S.

Our states

Death growth rates

  • This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
    • There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
  • Note that we’re charting growth rate and not a count of deaths, so don’t think of these as the standard “curve” that we hear about in the news and that we want to flatten. Instead, these growth rate charts help track more precisely what we can only estimate when we see those other curves. For these growth rate charts, if the line is above zero, the metric we are tracking (total or new deaths) is continuing to grow. If the growth rate line is going up, it’s growing more quickly each day; if it’s going down but still above zero, it’s growing less quickly (but still growing). Only when the growth rate lines go below zero has the metric stopped growing.
  • Each of these two lines uses rolling windows to calculate a growth rate for that particular metric. I do the calculation differently for each to smooth out some of the large day-to-day discrepancies in new death reporting at the state level.
    • For total deaths, the trendlines are a rolling 3-day average of daily growth rates in total deaths. We want to see these decline (and almost all are), but they can’t go below zero. This is because we’re tracking growth rate and a growth rate line below zero would mean total deaths have gone down, which can’t happen. They can only grow less quickly, which means we want to see the total death line get as close to zero as possible.
    • For new deaths, the trendlines show a rolling 3-day average of daily growth rate in the rolling 7-day average of new deaths. Including two rolling periods in this average helps smooth out crazy spikes at the state level that result from large day-to-day changes. Unlike the lines for total deaths, we want to watch for the lines for new deaths to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis.

U.S.

Our states

By population rankings

This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.

States

  • This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
  • For each metric, in addition to the tables, the trends for the top states are plotted over time.
    • We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.

Total confirmed cases

Table of total confirmed cases per million residents (all 50 states)
Ranking State Cases Per Million
1 North Dakota 127,326
2 South Dakota 121,380
3 Rhode Island 106,097
4 Utah 105,639
5 Tennessee 102,438
6 Arizona 100,926
7 Wisconsin 100,308
8 Iowa 99,839
9 Nebraska 97,338
10 Arkansas 95,164
11 Oklahoma 95,129
12 Kansas 93,468
13 Indiana 91,802
14 Alabama 90,942
15 Idaho 89,939
16 Mississippi 89,578
17 Nevada 88,613
18 Wyoming 88,382
19 Illinois 87,677
20 Montana 86,312
21 Louisiana 83,583
22 South Carolina 82,285
23 California 81,850
24 New Mexico 81,215
25 Minnesota 80,955
26 Georgia 80,573
27 Kentucky 79,278
28 Missouri 79,110
29 Texas 79,011
30 Florida 77,650
31 Delaware 77,523
32 New Jersey 75,626
33 Ohio 74,677
34 Massachusetts 73,439
35 Alaska 72,644
36 New York 69,856
37 North Carolina 69,670
38 Connecticut 68,689
39 Colorado 67,838
40 West Virginia 65,272
41 Pennsylvania 63,922
42 Michigan 60,164
43 Maryland 57,038
44 Virginia 56,625
45 District of Columbia 50,584
46 New Hampshire 46,459
47 Washington 40,431
48 Puerto Rico 39,353
49 Oregon 33,040
50 Maine 28,052
51 Vermont 18,085
52 Hawaii 17,849

New confirmed cases

Table of new cases per million residents: rolling 3-day average (all 50 states)
Ranking State New Cases Per Million
1 Rhode Island 837
2 Arizona 779
3 Connecticut 662
4 South Carolina 639
5 New York 606
6 Louisiana 595
7 California 591
8 Virginia 572
9 Texas 561
10 Georgia 547
11 Delaware 539
12 New Jersey 532
13 Oklahoma 528
14 North Carolina 490
15 Massachusetts 487
16 Arkansas 463
17 Kentucky 458
18 Alabama 439
19 Florida 432
20 West Virginia 414
21 Mississippi 400
22 Utah 393
23 New Hampshire 391
24 Ohio 372
25 Tennessee 367
26 Pennsylvania 339
27 Wyoming 327
28 Nevada 326
29 Indiana 318
30 Kansas 308
31 Maryland 295
32 District of Columbia 294
33 Missouri 290
34 Maine 275
35 New Mexico 272
36 Illinois 262
37 Iowa 251
38 Montana 249
39 Idaho 246
40 Colorado 244
41 Wisconsin 231
42 Puerto Rico 208
43 Vermont 201
44 Nebraska 199
45 Michigan 184
46 Washington 165
47 Minnesota 158
48 South Dakota 157
49 Alaska 147
50 Oregon 138
51 North Dakota 125
52 Hawaii 75

Total deaths

Table of total deaths per million residents (all 50 states)
Ranking State Deaths Per Million
1 New Jersey 2,376
2 New York 2,173
3 Massachusetts 2,063
4 Rhode Island 2,006
5 Mississippi 1,966
6 Connecticut 1,944
7 South Dakota 1,927
8 North Dakota 1,889
9 Louisiana 1,854
10 Arizona 1,715
11 Illinois 1,645
12 Pennsylvania 1,631
13 Arkansas 1,554
14 Michigan 1,531
15 New Mexico 1,513
16 Indiana 1,456
17 Iowa 1,423
18 Alabama 1,406
19 Tennessee 1,329
20 Nevada 1,328
21 South Carolina 1,277
22 District of Columbia 1,258
23 Kansas 1,243
24 Georgia 1,230
25 Texas 1,225
26 Florida 1,195
27 Missouri 1,153
28 Maryland 1,151
29 Montana 1,109
30 Minnesota 1,094
31 Delaware 1,093
32 Wisconsin 1,076
33 West Virginia 1,075
34 Wyoming 1,029
35 Nebraska 1,026
36 Colorado 975
37 California 967
38 Idaho 946
39 Ohio 928
40 Kentucky 843
41 North Carolina 842
42 Oklahoma 839
43 New Hampshire 731
44 Virginia 723
45 Puerto Rico 558
46 Washington 557
47 Utah 503
48 Oregon 452
49 Maine 415
50 Alaska 343
51 Hawaii 281
52 Vermont 274

New deaths

Table of new deaths per million residents: rolling 3-day average (all 50 states)
Ranking State New Deaths Per Million
1 Alabama 16
2 Tennessee 16
3 Hawaii 15
4 Arizona 14
5 Arkansas 14
6 Wyoming 14
7 Montana 13
8 Rhode Island 13
9 California 11
10 Mississippi 11
11 Connecticut 10
12 West Virginia 10
13 Delaware 9
14 Louisiana 9
15 New York 9
16 Pennsylvania 9
17 District of Columbia 8
18 Kentucky 8
19 Nevada 8
20 New Mexico 8
21 Florida 7
22 Georgia 7
23 Massachusetts 7
24 Missouri 7
25 Oklahoma 7
26 Texas 7
27 Maryland 6
28 New Jersey 6
29 North Carolina 6
30 South Carolina 6
31 Illinois 5
32 Indiana 5
33 Nebraska 5
34 Ohio 5
35 Michigan 4
36 Wisconsin 4
37 Colorado 3
38 Idaho 3
39 Maine 3
40 New Hampshire 3
41 South Dakota 3
42 Utah 3
43 Virginia 3
44 Kansas 2
45 Minnesota 2
46 Oregon 2
47 Washington 2
48 North Dakota 1
49 Puerto Rico 1
50 Alaska 0
51 Iowa 0
52 Vermont 0

Counties

  • This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
    • Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
  • In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.

Confirmed cases

Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Cases Per Million Raw Ranking Percentile
Crowley Colorado 291,371 1 99
Dewey South Dakota 234,895 2 99
Chattahoochee Georgia 234,162 3 99
Lincoln Arkansas 231,726 4 99
Bent Colorado 230,411 5 99
Davidson Tennessee 119,670 243 92
Richland South Carolina 82,574 1410 55
York South Carolina 75,753 1766 43
Orange California 75,314 1782 43
Pierce Washington 37,737 2890 8

Our county percentiles over time

Deaths

Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
County State Deaths Per Million Raw Ranking Percentile
Gove Kansas 8,346 1 99
Jerauld South Dakota 7,948 2 99
Dickey North Dakota 6,568 3 99
Gregory South Dakota 6,452 4 99
Grant Nebraska 6,421 5 99
Davidson Tennessee 1,031 1869 40
Richland South Carolina 955 1991 36
Orange California 872 2108 32
York South Carolina 758 2276 27
Pierce Washington 497 2647 15

Our county percentiles over time

Raw counts

Total confirmed cases

U.S.

Our states

Our counties

New confirmed cases

U.S.

Our states

Our counties

Total deaths

U.S.

Our states

Our counties

New deaths

U.S.

Our states

Our counties

Stay-at-home comparisons